This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more. As open source software, you will always have it available throughout your working life. It can also be used from the command line, program files or a new type of interface known as a Jupyter notebook (which is freely available as a service from JuliaBox.com).
Julia is designed to address the requirements of high-performance numerical and scientific computing while also being effective for general-purpose programming. You will be able to access all the available processors and memory, scrape data from anywhere on the web, and have it always accessible through any device you care to use as long as it has a browser. Join us to discover new computing possibilities. Let's get started on learning Julia.
By the end of the course you will be able to:
- Programme using the Julia language by practising through assignments
- Write your own simple Julia programs from scratch
- Understand the advantages and capacities of Julia as a computing language
- Work in Jupyter notebooks using the Julia language
- Use various Julia packages such as Plots, DataFrames and Stats
The course is delivered through video lectures, on-screen demonstrations, quizzes and practical peer-reviewed projects designed to give you an opportunity to work with the packages.

From the lesson

Structuring data and functions in Julia

As a scientific computing language, Julia is well suited to the task of working with data. In this last module, we elaborate on the two most important concepts in Julia, arrays and functions. They are the fundamental building blocks of holding and manipulating data. You should see this week as offering you a chance to further explore concepts introduced in week one and two. You will also be introduced to more efficient ways of managing and visualizing your data. By the end of this module, you will be able to: 1. Apply and understand how to work with arrays 2. Practice Julia functions 3. Explore extension packages 4. be familiar with the Dataframes package 5. Plot a variety of data from the dataset, ready for publication.